Centre for Nutrition Modelling, Department of Animal Biosciences, University of Guelph, N1G 2W1, Guelph, Ontario, Canada; Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, N1G 2W1, Guelph, Ontario, Canada.
Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, N1G 2W1, Guelph, Ontario, Canada.
J Dairy Sci. 2021 Aug;104(8):9304-9315. doi: 10.3168/jds.2020-20010. Epub 2021 Apr 30.
Genetic selection for improved feed efficiency in dairy cattle has received renewed attention over the last decade to address the needs of a growing global population. As milk yield is a critical component of feed efficiency metrics in dairy animals, our objective was to evaluate the associations between feed efficiency in primiparous Holstein cattle and parameters of a mathematical model describing individual lactation curves. The Dijkstra lactation curve model was fit to individual lactation records from 34 Holstein heifers with previously estimated measures of feed efficiency. We found that the optimal fit of the Dijkstra model was achieved using daily milk yield records up to 21 d in milk to capture the rise to peak milk yield and using monthly dairy herd improvement records for the remainder of lactation to accurately characterize lactation persistency. In the period of lactation before peak milk yield, improved feed efficiency was associated with a faster increase in daily milk yield over a shorter period of time at the expense of increased mobilization of body reserves; this serves to reinforce the concept that dairy cattle are primarily capital breeders versus income breeders. Feed efficiency in the period following peak lactation, as measured by gross feed efficiency, return over feed costs, and net energy efficiency of lactation, was positively associated with higher peak milk yield. The findings in early lactation suggest that estimates of feed efficiency could be improved by evaluating feed efficiency relative to conception, rather than parturition and lactation, to better account for the energy stored and released from body reserves in capital breeding.
在过去的十年中,为了满足全球人口增长的需求,人们对提高奶牛饲料效率的遗传选择重新产生了兴趣。由于产奶量是奶牛饲料效率衡量标准的关键组成部分,我们的目标是评估初产荷斯坦奶牛饲料效率与描述个体泌乳曲线的数学模型参数之间的关系。使用先前估计的饲料效率测量值,拟合了 34 头荷斯坦小母牛的个体泌乳记录的 Dijkstra 泌乳曲线模型。我们发现,使用在泌乳期内 21 天内的每日产奶量记录,以及在泌乳期剩余时间内使用每月奶牛群改良记录,可以达到 Dijkstra 模型的最佳拟合,从而可以准确地描述泌乳持续性。在达到产奶高峰之前的泌乳期间,饲料效率的提高与在较短时间内更快地增加每日产奶量有关,代价是增加体储备的动员;这进一步强化了这样一个概念,即奶牛主要是资本繁殖者,而不是收入繁殖者。通过与受孕而非分娩和泌乳相关联来评估饲料效率,用总饲料效率、饲料成本回报和泌乳净能量效率来衡量的泌乳后期的饲料效率与更高的产奶高峰呈正相关。在泌乳早期的发现表明,通过评估相对于受孕的饲料效率,而不是相对于分娩和泌乳的饲料效率,来提高饲料效率的估计,可以更好地考虑到资本繁殖中从体储备中储存和释放的能量。